Lenny's Podcast: Product | Career | Growth
00:06:13 · Noam Segal
[00:06:13] S0: Well, first I'll say that you and I both noticed an incredible post from Elena Verna a couple of days before this pod was recorded. And, she's talking about the AI confidence theater, and how in conversations these days in tech, everything is dead, first of all. Engine coding is dead, design is dead, SaaS is dead, et cetera. Obviously that's not true. So what you're about to see in these results is the best picture we could provide, and probably the best picture anyone's provided so far, of how people are really feeling about AI. And to me, this also ties to the fact that, if you're watching this and you work in tech, you probably answer some sort of biannual culture Amp style survey about how you are feeling, but the questions don't really dive any deeper than the effectiveness of your manager or leadership at the company you work at. Whereas, the big picture in this survey, and I think the thing that stood out to us the most, is how bifurcated the workforce is right now. And what you're going to see is that AI has an outlier level, outsize impact, on how people feel about their work more so than any other characteristic of their job, whether it's their role, the company they work for, the company size, their level, et cetera. Half of the people in tech are feeling incredible; energized, amplified, excited about the technology and the future of their role. And the other half feel like the future is unclear, they feel destabilized, they feel diminished, other negative emotions around that. It's a very interesting picture that really cuts the tech workforce in half, and that's what we'll see in a second.
00:08:22 · Lenny Rachitsky
[00:08:22] S1: It feels so like, yes, this feels correct as we look at people in tech. It just is so clear that this happening. And what's interesting is it's fifty fifty in the results. I didn't expect to be so even. That was a really interesting takeaway.
00:08:36 · Noam Segal
[00:08:36] S0: It's 50-50. When you dive a little bit deeper into the data, there is some nuance there. So we're looking at this slide with the question that you and I both decided to answer the survey, which is how has AI shifted your professional identity, if at all? And I'll actually call out, first of all, that only 3% of people reported that AI hasn't shifted their identity. So clearly AI has changed how we each view ourselves. That's first of all. But then to your point, the most prominent thing here is that 50% of people in tech are feeling amplified. They feel like they can do more. They feel like they can do better. It's a wholly positive emotion, and it's great. It's great for them. But the other half of tech divide into three distinct groups. The first group is people who feel like their role is being redefined. That group doesn't actually have that much clarity or specific positive or negative emotions around what's happening. They just don't really understand it. It's a very mixed bag type of emotion, where it's very clear to me that my role is fundamentally changing, but I don't really know what it means. And that's 27% of our sample. Then, as we go down the line, we have two groups who have clear negative emotions around what's going on. The first group, 14% of people feel destabilized. The ground is shaking beneath them. They have very little clarity on what's going on. They have high anxiety levels. They report having very negative and pessimistic views of what's to come. And then, 5% of people feel diminished. They feel like the great powers of AI have taken something away from them, and something that obviously is never going to come back, because what's the saying, AI and AI models are the worst today that they'll ever be. They're only getting better. So people who feel diminished now will only feel more diminished in the future, probably.
00:10:57 · Lenny Rachitsky, Noam Segal
[00:10:57] S1: Super. So following that thread- [00:10:59] S0: Sorry for the bad news. [00:11:00] S1: Sorry for the bad news. There's some good news here. So following that thread, these buckets correlate super strongly with, basically every other measure of how people are doing. See this kind of regression on just every other core question you asked, and it's so interesting to see how connected these are.
00:11:20 · Noam Segal
[00:11:20] S0: Yeah. And just to put a couple of statistical terms on this to clarify how big the effect is. In tech, we are somewhat obsessed with the notion of statistical significance. But the thing about statistical significance is that, if you have a large enough sample, you can reach that type of significance, regardless of how much the effect matters practically. A better way to look at things is using an effect size measure, like Cohen's d in this case. And what effect size tells you is, practically, how much does this thing matter? So for example, last year, a couple of the largest effects we saw were number one, your manager. Who your mager is and how effective they are matches a ton, to how much you are enjoying your job and how optimistic you are and how burnt out you are or not. And we'll see some of that later on. And the second large effect we found was the founder happiness effect. Founders, these people who are currently founders and in their journey of running a startup, are incredibly happy, probably because they have lots of agency and autonomy, relatively to the typical employee. This finding, this insight around the impact of AI on your identity, and on every single other variable around your job, is about three times as large as those other effects. So this technology, this era that we're in, is having an outlier level, outsized impact on how people are feeling about work, more so than anything else we've seen.
00:13:02 · Lenny Rachitsky, Noam Segal
[00:13:02] S1: So let's actually look at that data of just how this sort of classification connects to just optimism, burnout, things like that. And we're going to come back to just what exactly is that divide, just the question to ask that tells you which side you're on, but let's look at this first. [00:13:16] S0: Yeah, so we'll dive into some of these things in a little more depth later on, but just to put it all together, what you're looking at here is the AI identity stance, and then a breakdown by your AI identity around career optimism, burnout, layoff worry. And, an interesting one for me, and we'll talk about this further, would you recommend your role to someone coming into the industry now? And what you can see is that as you move from the people who feel amplified to the people who feel diminished, career optimism goes down significantly. Burnout, or reports of burnout, go up significantly. Layoff worry also rises significantly. And perhaps the most significant finding of them all, is that people would not recommend junior people, early career people, entering into the tech workforce at this moment given what's happening with AI. And you are seeing these very linear, clear, and organized effects, which just demonstrates to you the impact that AI is having on all of these different variables. [00:14:38] S1: And what I love is you took all of all these data points, and you've created these four archetypes of people today. And I feel like everyone listening is going to be like, "Okay, that's me." So let's go through that.